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支持再制造的选择性并行拆卸序列规划方法

田永廷1), 张秀芬1)*, 徐劲芳2), 李治国1)
1) (内蒙古工业大学机械学院 呼和浩特 010051)2) (东北大学机械工程与自动化学院 沈阳 110004)
分类号: TH122 DOI: 10.3724/SP.J.1089.2018.16317
出版年,卷(期):页码: 2018 , 30 ( 3 ): 531-539 田永廷
摘要: 选择性并行拆卸是再制造的关键步骤, 为提高再制造拆卸效率, 提出一种基于遗传算法的选择性并行拆卸序列规划方法. 根据产品拓扑结构和拆卸优先级关系构建了产品拆卸混合图模型, 并表示为关联矩阵、邻接矩阵和约束矩阵; 提出了目标驱动推演法的目标组件初始拆卸解集合获取方法, 由此构建初始种群, 并利用关联矩阵剔除不合理解, 以提高算法的收敛速度; 改进了选择、交叉、变异等染色体进化规则, 由此求出了目标组件(近似)最优的并行拆卸序列. 最后, 通过实例验证了该方法的可行性和有效性.
关键词: 再制造; 拆卸序列规划; 遗传算法; 选择性并行拆卸
Selective Parallel Disassembly Sequence Planning Method for Remanufacturing
Tian Yongting1), Zhang Xiufen1)*, Xu Jinfang2), and Li Zhiguo1)
1) (The College of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051) 2) (The College of Mechanical Engineering and Automation, Northeastern University, Shenyang 110004)
abstract: Selective disassembly parallel is a key step of remanufacturing. To improve remanufacturing disassembly efficiency, a selective parallel disassembly sequence planning method is proposed based on genetic algorithm. According to the product topology and disassembly precedence relation, a product’s disassembly hybrid graph model (DHGM) is constructed. Furthermore, the DHGM is expressed as the correlation matrix, the adjacency matrix and constraint matrix. The initial population of the objective component is constructed based on an object-driven deduction method presented in this paper. In order to improve the convergence speed of the algorithm, the unreasonable disassembly sequences are eliminated via the correlation matrix. The chromosome evolution rules, such as selection, crossover, and mutation operator are improved to obtain the (approximate) optimal selective parallel disassembly sequences of the objective component. Finally, a case study validates the method proposed in the paper.
keyword: remanufacturing; disassembly sequence planning; genetic algorithm; selective parallel disassembly
 
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